US7961866B1 - Method and computer readable medium for geographic agent routing - Google Patents

Abstract

A method and computer readable medium for routing a call to geographically dispersed agents based on agent skill-set, agent location and caller location that results in the call being delivered to the best available agent. The computer readable medium and method are utilized with a system comprised of a call center application module coupled to a database module with a communications network being used to couple incoming calls from customers with the best available agent. A database contains a ranking of available agents, based on a dataset including information regarding skill-set, previous interaction with the customer, proximity to the customer, language capability, current availability, and the like. The method chooses the best available agent to service a customer call based on the agent rankings. In the case where the customer has a preference for proximity of the agent to the customer, the system adjusts the agent rankings according to the agent's distance from the customer prior to making a selection.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

The present patent application is related to and filed on even date herewith as pending patent application Ser. No. 11/421,841, entitled “System for Geographic Agent Routing” which is incorporated in its entirety by reference herein.

BACKGROUND OF THE INVENTION

The present invention relates to the general field of routing agents from call centers and in particular to a method and computer readable medium for optimally routing such agents.

The present invention comprises a method and computer readable media (or software) for routing a call or other communication to a best available individual, such as a call center agent, customer service representative, and the like, who has a certain relationship with a caller, such as, for example, a physical proximity between the individual and the caller.

Currently, many businesses utilize call centers, each with multiple agents, to provide customer service. Typically, businesses employ multiple physical call centers to enable around-the-clock call handling and to utilize cheaper labor markets. Current call center applications enable call routing by a number of methods including time-of-day (TOD), agent availability, caller location and agent skill-set. In some cases, these methods can be combined to form a routing plan. There are limitations to this approach however, including the need to group agents at certain physical locations and the strict prioritization of one routing method over another. These limitations may result in a customer who is not very comfortable with his agent due to accent, lack of local knowledge, etc.

Therefore, what is needed to overcome the aforementioned limitations, is a computer readable medium utilized in conjunction with a call center system or with a system utilized by an agent based at a residence or other non-call center location, and a call routing method for geographically dispersed agents, based on agent skill-set, agent location, and/or caller location that results in delivery of an incoming call to a best available agent, while allowing a certain preference towards agents who are geographically closer to the caller.

SUMMARY OF THE INVENTION

The present invention, accordingly, provides a computer readable medium and a method for routing calls to geographically dispersed agents based on agent skill-set, agent location and/or caller location, that results in call or non-voice message delivery to a best available agent.

In a preferred embodiment of the invention, a method chooses a best available agent to service a customer call based on the ranking of all agents. If a customer has a preference for proximity of the agent to the customer, the system adjusts the agent rankings according to their distance from the customer prior to making a selection. The method of the present invention is implemented via a call center system, which is comprised of a call center application module coupled to a database module. A communications network is used to couple incoming calls from customers, as well as various call center agents, to the system. The communications network will accommodate both static (fixed location) and dynamic (wireless) communications. A database contains a ranking of available agents based on a dataset including information regarding skill-set, previous interaction with the customer, proximity to the customer, language capability, current availability, and the like.

In operation, when a customer places a call (for example, to a system utilizing the present method and computer readable medium), he/she specifies a proximity preference factor (PPF) from 0%-100%. If the PPF is 0% then the customer does not care about the distance between the customer (caller) and the agent, then the system selects an agent solely on the initial agent ranking. However, if the customer specifies a PPF >0 with an agent range preference (ARP), then a distance adjustment is made, as follows: First, an agent ranking range (ARR) is calculated by subtracting the lowest agent ranking from the highest agent ranking. Then a distance adjustment is made for each agent within the ARP according to the formula:
ARR*PPF*(ARPmax+ClosestDistanceInARR−AgentDistance)/ARPmax,
and the final ranking is determined by subtracting the distance adjustment from the initial ranking for each agent. The agent with the lowest ranking is then assigned to service the call.

The present invention provides a fast, automated selection of the best available agent to service an incoming request based on the customer's preferences.

BRIEF DESCRIPTION OF THE DRAWINGS

The above listed and further advantages of the invention may be better understood by referring to the following description in conjunction with the accompanying drawings, in which:

FIG. 1 depicts a call center system for implementing a first method of the present invention;

FIG. 2 depicts a flowchart illustrating the method steps for agent selection in accordance with a first embodiment of the present invention;

FIG. 3 depicts a first exemplary configuration in accordance with a first embodiment of the present invention;

FIG. 4 depicts a second exemplary configuration in accordance with a first embodiment of the present invention;

FIG. 5 depicts a third exemplary configuration in accordance with a first embodiment of the present invention;

FIG. 6 depicts a fourth exemplary configuration in accordance with a first embodiment of the present invention; and

FIG. 7 depicts a flowchart for agent selection in accordance with a preferred embodiment of the present invention;

FIG. 8 depicts a first exemplary configuration in accordance with a preferred embodiment of the present invention;

FIG. 9 depicts a second exemplary configuration in accordance with a preferred embodiment of the present invention;

FIG. 10 depicts a third exemplary configuration in accordance with a preferred embodiment of the present invention;

FIG. 11 depicts a fourth exemplary configuration in accordance with a preferred embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

In the description that follows, like elements are marked throughout the specification and drawings with the same reference numerals, respectively. The drawing figures are not necessarily to scale and certain elements may be shown in generalized or schematic form in the interest of clarity and conciseness. Certain routine steps, in flow charts, normally included in the operation of the present invention have been omitted in the interest of conciseness. However, the steps which include methodology in accordance with the present invention are indicated in the charts. As is conventional, the letters Y and N designate “yes” and “no”, respectively.

Referring now toFIG. 1, theoverall system10 for implementing a first method of the invention includes acall center system12, which is comprised of a callcenter application module14 and adatabase module16 containing customer data, agent data, and the like. It should be noted that the functionality performed by themodules14,16 can be performed by one of these modules or by another module (not shown) that may be a part of thecall center system12 or communicate with thesystem12. Thesemodules14,16 may include software, hardware, firmware, and/or a combination of software, hardware, and/or firmware.

Acustomer18, who may desire to purchase a product or a service, for example, communicates (for example, calls, emails, FAX, etc.) with a call center agent20-24 via thecall center system12 over acommunications network26. Thenetwork26 may be a Public Switched Telephone Network (PSTN), an Internet Protocol Network, a wired network, a wireless network, or any combination of these networks. Thecall center system12 of the present invention, uses the procedure offlowchart28, described herein, along with computer readable media of the present invention to determine the best available agent from a set of geographically dispersed agents20-24 for servicing a customer call, and routes the call accordingly to a particular agent. For purposes of this example only, the call is depicted as being routed toagent24.

Referring now toFIG. 2, a first agent selection procedure is implemented using a computer readable medium of the present invention. The procedure or method begins30 by calculating32 an initial ranking for each agent based on skill-set and/or other attributes, which include race, sex, etc.

The method proceeds by retrieving 34 two pieces of data associated with the caller. The first is a Proximity Preference Factor (PPF). This allows the caller to weight the importance of proximity in agent selection. A PPF of 100% turns even the worst agent into the best agent if they happen to be the closest. A PPF of 50% turns the worst agent who happens to be the closest to an agent better than 50% of the available agents. A PPF of 0% effectively disables distance factors in agent selection.

The second piece of retrieved data is an Agent Range Preference (ARP). This allows a customer to specify a distance range in which proximity is going to be given consideration. The ARP consists of a minimum and a maximum distance value. The minimum can be used to filter out agents who might be calling themselves. The maximum can be used to stop giving preference to agents outside a particular range. For example, an agent 2500 miles away is probably no more preferable to an agent 2600 miles away.

Once the data has been retrieved, adecision point36 is reached. If the PPF=0, then agent distance is not a factor for this caller. Given this, the method proceeds toagent selection52 based on the initial agent ranking.

However, if the PPF>0, then distance is a factor for this caller. Given this, a distance between the caller and each agent is calculated38. This can be done with simple calculations that take advantage of static (address, NPA-NXX, zip code, etc.) and/or dynamic (cell site, GPS coordinates, etc.) data associated with the caller and the available agents.

Once complete, the method determines40 if there is at least one agent whose distance falls within the ARP. If not, then the distance of the available agents is still not a factor, so the method proceeds toagent selection52.

If there is at least one agent that falls within the ARP, then the method proceeds to calculate anARP Delta42. The ARP delta is the difference between the maximum and the minimum ARP distance values as shown by the formula below:
ARP Delta=ARP Maximum−ARP Minimum  (1)

The ARP Delta is then used to calculate 44 an Adjusted Distance Scale (ADS), which is determined by subtracting the closest agent distance (CAD) within the ARP range from the ARP Delta as shown by the formula below:
ADS=ARP Delta−Closest Agent Distance  (2)

The method continues by calculating46 an Agent Ranking Range (ARR), which is determined by subtracting the lowest agent ranking from the highest agent ranking or setting the value of equal to 1 if the result of the subtraction is zero, as derived by the following formula:
ARR=Maximum(1,High Agent Ranking−Lowest Agent Ranking)  (3)

Once the ARP Delta, ADS and ARR have been calculated (42-46), a ranking adjustment is calculated48 for each agent whose distance falls within the ARP. The adjustment is calculated using the formula:
Adjustment=ARR*PPF*(ARPDelta−AgentDistance)/ADS  (4)

This formula uses the Agent Ranking Range (ARR) and the callers Proximity Preference Factor (PPF) to scale the adjustment. The closest agent will receive the largest adjustment. The furthest agent will receive the smallest adjustment.

Once the adjustments have been calculated, the method proceeds to calculate 50 the final ranking of all the agents. This calculation is performed by subtracting any adjustment from the initial ranking determined previously32.

With the final rankings calculated, the selection ends54 by selecting52 the lowest ranking and therefore, the best agent.

In order to understand the benefits of the method, several applications of the invention in various caller/agent configurations will now be described. Referring now toFIG. 3, in a first exemplary configuration, theinitial ranking62 of the various agents70-78 listed in theagent column60 is determined as listed. Once determined, thePPF80 and theARP82 submitted by the call center application are retrieved. In this case the PPF is 50% and the ARP is 100 to 500. Since the callers PPF (50%) is greater than zero, thedistance64 between the caller and each agent70-78 is calculated.

Three agents,72-76 are within the ARP range, so their rankings must be adjusted. To do this, theARP Delta86 is calculated first. As shown by theformula 1, the ARP delta is calculated by subtracting the agent range minimum from the agent range maximum. In this case, given that the maximum is 500 and the minimum is 100 (FIG. 3-82), theARP Delta86 is 400. The method then proceeds to calculate theADS88, which is calculated byformula 2. In this case, the closest agent within the range isTom87 at 120 miles, so theADS88=400−120=280.

The procedure then proceeds using formula 4 to calculate thedistance adjustment66 for each agent72-76 within the ARP84 range. Note thatagents70,78 outside the ARP range receive a 0 adjustment. The adjustment values66 are then calculated according to formula 4.Tom72 receives the biggest adjustment, 12, as he is closest to the caller. The figure is arrived at by the following calculation of equation 4: 24*0.50*(400−120)/280=12. The ARR is 24 and 0.50 is the callers' 50% PPF. The remaining within-range agent adjustments are calculated similarly, withJoe74 receiving an adjustment of 7.3 andMary76 receiving an adjustment of 6.4.

Thefinal rankings68 for the agents are then calculated by subtracting theadjustment value66 from theinitial ranking62. The result in this exemplary configuration is thatMary76 has the lowest final ranking, 11.6, and therefore is chosen as the best agent. Note that Mary is not the closest agent within the agent range preference, but the adjustment to her already low initial ranking of 18 moved her ahead of Jim, the agent with the best initial ranking.

Referring now toFIG. 4, in a second exemplary configuration, the caller'sPPF110 is now set to 100, indicating that proximity is of utmost importance to the caller. In this case, since the PPF=100, instead of 50, the PPF factor in formula 4 equals 1, instead of 0.5. Here, theARP112 is 100-500 so that theARP delta116 is 400, minimum distance within theARP117 is 120, theARR114 is 24, and theADS118 is 280. Again,Jim100 andFrank108 are outside theARP112 range and receive zeroadjustments96.Adjustments96 of 24 forTom102, 14.6 forJoe104, and −4.3 forMary106 are calculated. The resultingfinal rankings98 depict that Joe has the lowest ranking and is therefore chosen as the best agent. Although Mary has a better initial ranking than Joe, Joe is closer than Mary and that is more important to the caller in this exemplary configuration.

Referring now toFIG. 5, in a third exemplary configuration, the caller'sPPF140 is again set to 50% and theARP142 is 100-400. However, theranking122 for theAgents120 showsJim130 at 20.3,Tom132 at 19.5,Joe134 at 20.1,Mary136 at 19.9, andFrank138 at 20.4. Since thedistances124 forJim130 andFrank138 are 20 and 450, respectively, these are outside theARP142 range of >100 and <400, so the adjustment for each of these two agents is set at zero. Furthermore, theARP delta146 is 300, the minimum distance withinARP147 is 120, and ADS148 is 180. In this case then, using formula (3) (ARR=Maximum (1, High Agent Ranking−Lowest Agent Ranking), theARR144 is calculated to be 1 as a result of theagent rankings122 being tightly packed. This results in anadjustment126 of 0.50 forTom132, 0.19 forJoe134, and 0.14 forMary136. The resultingfinal rankings128 depict that Tom has the lowest ranking and is therefore chosen as the best agent. In this example, Tom had both the best initial ranking and the best adjusted ranking.

Referring now toFIG. 6, a fourth exemplary configuration is shown, which has the sameinitial ranking122 anddistance124 for the agents130-138 as for the first exemplary configuration discussed inFIG. 3. However, here the caller'sPPF170 is now set to 90%, indicating that proximity is of fairly high importance to the caller, theARP172 is 0-600, theARR174 is 24, theARP delta176 is 600, the minimum distance inARP177 is 20, and theADS178 is 580. Although this example is much like the first exemplary configuration, now all five agents160-168 are within theARP172 range and therefore need to be adjusted. In this case, since the PPF=90%, instead of 50%, the PPF factor in formula 4 equals 0.9, instead of 0.5. This results inadjustments156 of 21.6 forJim160, 17.9 forTom162, 13.8 forJoe164, 13.0 forMary166, and 3.7 forFrank168. The resultingfinal rankings158 depict thatJim160 with and afinal ranking158 of −6.6 has the lowest ranking after adjustment and is therefore chosen as the best agent.

FIG. 7 shows the flowchart for a preferred embodiment of the agent selection procedure of the present invention. The method uses the procedure illustrated inflowchart230. Here, the method begins232 by calculating234 an initial ranking for each agent based on skill-set and/or other attributes, which include race, sex, etc.

The method proceeds by retrieving236 two pieces of data associated with the caller. The first is a Proximity Preference Factor (PPF). This allows the caller to weight the importance of proximity in agent selection. A PPF of 100% turns even the worst agent into the best agent if they happen to be the closest. A PPF of 50% turns the worst agent who happens to be the closest to an agent better than 50% of the available agents. A PPF of 0% effectively disables distance factors in agent selection.

The second piece of retrieved data is an Agent Range Preference (ARP). This allows a customer to specify a distance range in which proximity is going to be given consideration. The ARP consists of a minimum and a maximum distance value. The minimum can be used to filter out agents who might be calling themselves. The maximum can be used to stop giving preference to agents outside a particular range. For example, an agent 2500 miles away is probably no more preferable to an agent 2600 miles away.

Once the data has been retrieved, adecision point238 is reached. If the PPF=0, then agent distance is not a factor for this caller. Given this, the method proceeds toagent selection248 based on the initial agent ranking.

However, if the PPF>0, then distance is a factor for this caller. Given this, a distance between the caller and each agent is calculated240. This can be done with simple calculations that take advantage of static (address, NPA-NXX, zip code, etc.) and/or dynamic (cell site, GPS coordinates, etc.) data associated with the caller and the available agents.

Once complete, the method determines242 if there is at least one agent whose distance falls within the ARP. If not, then the distance of the available agents is still not a factor, so the method proceeds toagent selection248.

However, if at least one agent falls within the ARP, then the method proceeds to calculate243 an Agent Ranking Range using the formula;
ARR=Highest Agent Ranking−Lowest Agent Ranking.  (5)

Next, this Agent Ranking Range is used to calculate adistance adjustment244 for each agent within the ARP, using the formula:
Adjustment=ARR*PPF*(ARPmax+ClosestDistanceInARR−AgentDistance)/ARPmax,  (6).

This formula uses the Agent Ranking Range (ARR) and the callers Proximity Preference Factor (PPF) to scale the adjustment. The closest agent will receive the largest adjustment. The furthest agent will receive the smallest adjustment.

Once the adjustments have been calculated, the method proceeds to calculate246 the final ranking of all the agents. This calculation is performed by subtracting each adjustment from the initial ranking determined previously234.

With the final rankings calculated, the selection ends250 by selecting248 the lowest ranking and therefore, the best agent.

Again, in order to understand the benefits of the method for this preferred embodiment of the invention, several applications of the invention in various caller/agent configurations will now be described. Referring now toFIG. 8, in a first exemplary configuration, theinitial ranking252 of the various agents260-268 listed in theagent column250 is determined as listed. Once determined, thePPF270 and theARP272 submitted by the call center application are retrieved. In this case the PPF is 50% and the ARP is 100 to 500. Since the callers PPF (50%) is greater than zero, thedistance254 between the caller and each agent260-268 is calculated. Finally, theARR274 is calculated as the Highest Ranked Agent−Lowest Ranked Agent. In this case, sinceTom262 is the highest ranked agent with a ranking of 39 andJim260 is the lowest ranked agent with a ranking of 15, the ARR=39−15=24 (5).

Since three agents,262-266 are within the ARP range, their rankings must be adjusted using formula (6), as follows to calculate thedistance adjustment256 for each agent262-266 within theARP272 range. Note thatagents260,268 outside the ARP range receive a 0 adjustment. The adjustment values256 are then calculated according to formula (6).Tom262 receives the biggest adjustment, 12, as he is closest to the caller. This figure is arrived at by the following calculation of formula (6):
Adjustment=24*0.50*(500+120-120)/500=12.
TheARR274 is 24 and thePPF270 is 0.50 or 50%. The remaining within-range agent adjustments are calculated similarly, withJoe264 receiving an adjustment of 9.4 andMary266 receiving an adjustment of 8.9.

Thefinal rankings258 for the agents are then calculated by subtracting theadjustment256 values from theinitial ranking252 values. The resulting final rankings 27.0 forTom262, 10.6 forJoe264, and 9.1 forMary266 depict thatMary266 has the lowest final ranking of 9.1 and is therefore chosen as the best agent.

Referring now toFIG. 9, in a second exemplary configuration, the caller'sPPF300 is now set to 100%, indicating that proximity is of utmost importance to the caller. In this case, since the PPF=100%, instead of 50%, the PPF factor in formula (6) equals 1.0, instead of 0.5. Here, theARP302 is 100-500 and theARR304 is 24. Again,Jim290 andFrank298 are outside theARP310 range and receive zeroadjustments286.Adjustments286 of 24 forTom292, 18.7 forJoe294, and 8.2 forMary296 are calculated using equation (6). The resultingfinal rankings288 of 15.0 forTom292, 1.3 forJoe294, and 9.8 forMary296 depict thatJoe294 has the lowest final ranking of 1.3 and is therefore chosen as the best agent. AlthoughMary296 has a better initial ranking thanJoe294, Joe is closer than Mary and that is more important to the caller in this exemplary configuration.

Referring now toFIG. 10, in a third exemplary configuration, the caller'sPPF330 is again set to 50% and theARP332 is 100-400. However, theinitial ranking312 for theAgents310 showsJim320 at 20.3,Tom322 at 19.5,Joe324 at 20.1,Mary326 at 19.9, andFrank328 at 20.4. TheARR334 is 0.9 determined as the difference between the highest and lowest ranking of 20.4 and 19.5. Since thedistances314 forJim320 andFrank328 are 20 and 450, respectively, and are outside theARP332 range of 100 and 400, the adjustment for each of these two agents is set to zero. Equation (6) is then used to calculate the adjustments for the remaining three agents, which results in anadjustment316 of 0.45 forTom322, 0.33 forJoe324, and 0.31 forMary326. The resultingfinal rankings318 of 19.05 forTom322, 19.8 forJoe324, and 19.6 forMary326 depict thatTom322 has the lowest ranking and is therefore chosen as the best agent. In this example, Tom had both the best initial ranking and the best adjusted ranking.

Referring now toFIG. 11, a fourth exemplary configuration is shown, which has the sameinitial ranking342 anddistance344 for the agents350-358 as for the first exemplary configuration discussed inFIG. 8. However, here the caller'sPPF360 is now set to 90%, indicating that proximity is of fairly high importance to the caller, theARP362 is 0-600, and theARR364 is 24. Although this example is much like the first exemplary configuration ofFIG. 9, now all five agents350-358 are within theARP362 range and therefore need to be adjusted. In this case, since the PPF=90%, instead of 50%, the PPF factor in formula (6) is set to 0.9. This results inadjustments346 of 21.6 forJim350, 18.0 forTom352, 14.0 forJoe354, 13.3 forMary356, and 4.3 forFrank358. The resultingfinal rankings348 of −6.60 forJim350, 21.0 forTom352, 6.0 forJoe354, 4.7 forMary356, and 15.7 forFrank358 depict thatJim350 with and afinal ranking348 of −6.6 has the lowest ranking after adjustment and is therefore chosen as the best agent.

Although embodiments of a method and computer readable medium for various embodiments of geographic agent routing have been described in detail herein, it will be appreciated that the present invention may provide applicable inventive concepts that can be embodied in a wide variety of specific contexts. For example, while the preferred embodiment of the invention has principally referenced a method for optimally routing agents it should be understood that the method may also be utilized for alternative applications, such as selecting particular computers, security systems, imaging systems, and the like. Also, a lesser or greater number of modules or components may be utilized in the system of the present invention to make the selection of the best available agent. The specific embodiments discussed herein are merely illustrative of specific ways to make and use the invention, and do not delimit the scope of the invention. Those skilled in the art will recognize that various substitutions and modifications and a lesser or greater number of modules or components may be utilized in the invention without departing from the scope and spirit of the appended claims.

Claims (8)

1. A method for routing a customer call to a best available agent, comprising:

receiving a call based on an initial agent ranking of all available agents, a caller's proximity preference factor, and an agent range preference;

coupling a plurality of incoming customer calls and existing call center agents;

providing an initial agent ranking based on a dataset including information of at least one from the group of: skill-set, previous interaction with a customer, language capability, race, sex, minimum distance from an agent to a customer, maximum distance from an agent to a customer, and current availability;

assigning an agent to service a customer based on an agent distance adjustment being made relative to a closest agent distance prior to assigning an agent to service a customer when said customer specifies an agent range preference; by

calculating an agent range preference delta by subtracting said minimum distance from an agent to a customer from said maximum distance from an agent to a customer;

calculating an adjusted distance scale by subtracting said minimum distance from an agent to a customer from said agent range preference delta;

calculating an agent ranking range parameter by subtracting said initial agent ranking having a lowest value from said initial agent ranking having a highest value;

determining a distance adjustment for each said agent within said agent range preference by multiplying said agent range preference times said proximity preference factor times a difference between said agent range preference delta and an agent distance to said customer and dividing by said calculated adjusted distance scale; and

calculating a final ranking by subtracting said distance adjustment from said initial ranking for each said agent.

2. The method ofclaim 1, wherein an agent is assigned to service a customer based on said initial agent ranking when said customer specifies no agent range preference indicating distance between said customer and said agent.

3. The method ofclaim 1, wherein customer communication devices provide capability for communications via at least one of: a landline phone call, an e-mail, a fax, Internet, a wireless phone call, a wireless intercom, and a wireless Internet.

4. The method ofclaim 1, wherein a distance between a customer and various available agents is determined using at least one of: an address, a NPA-NXX, a Zip Code, cell cite locations and GPS coordinates.

5. A method for routing a customer call to a best available agent, comprising:

receiving a call based on an initial agent ranking of all available agents, a caller's proximity preference factor, and an agent range preference;

coupling a plurality of incoming customer calls and existing call center agents;

providing an initial agent ranking based on a dataset including information of at least one from the group of: skill-set, previous interaction with a customer, language capability, race, sex, minimum distance from an agent to a customer, maximum distance from an agent to a customer, and current availability;

assigning an agent to service a customer based on an agent distance adjustment being made relative to a closest agent distance prior to assigning an agent to service a customer when said customer specifies an agent range preference; by

calculating an agent ranking range parameter by subtracting said initial agent ranking having a lowest value from said initial agent ranking having a highest value;

determining a distance adjustment for each said agent within said agent range preference by multiplying said agent range preference times said proximity preference factor times a term comprised of (agent range preference—ARP) ARPmax plus a closest distanceARP minus an agent distance and dividing the result by said ARPmax; and

calculating a final ranking by subtracting said distance adjustment from said initial ranking for each said agent.

6. The method ofclaim 5, wherein an agent is assigned to service a customer based on said initial agent ranking when said customer specifies no agent range preference indicating distance between said customer and said agent.

7. The method ofclaim 5, wherein customer communication devices provide capability for communications via at least one of: a landline phone call, an e-mail, a fax, Internet, a wireless phone call, a wireless intercom, and a wireless Internet.

8. The method ofclaim 5, wherein a distance between a customer and various available agents is determined using at least one of: an address, a NPA-NXX, a Zip Code, cell cite locations and GPS coordinates.

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